Preston Parry
Mad Scientist at Climate Change Research
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPreston Parry is an experimental-minded machine learning and data science leader with 11 years of experience blending hands-on engineering, research, and product impact to tackle hard problems. Currently leading climate-focused experiments as a "Mad Scientist" in Oakland, he couples data-driven thinking with chemistry- and infrastructure-oriented projects aimed at scalable carbon capture and revenue-positive climate solutions. Formerly DoorDash’s first data scientist and later Lead Data Scientist, he built production ML systems that materially improved core business metrics and democratized ML across teams. He teaches and mentors regularly, having run intensive engineering instruction at Telegraph Academy and led ML education programs at industry scale. An active contributor to scikit-learn documentation, he also brings maker/robotics chops from hands-on projects and a pragmatic startup mindset from roles across analytics, product, and operations. Outside work he’s a rock climber, biker, and community builder—fueling a curious, iterative approach to research and engineering.
11 years of coding experience
5 years of employment as a software developer
Revere High SchoolComputer Science, Computer Science at Hack ReactorB.S. Business Economics, B.S. Business Economics at Miami University
English, python, javascript, r, sql
Stackoverflow
1,054reputation
168kreached
11answers
0questions
jupyter-notebook
top-5%
scikit-learn
top-5%
Github Skills (16)
technical-writing10
documentation10
scikit-learn9
python9
jupyter-notebook9
data-science7
machine-learning7
jupyter6
gdax-api6
javascript6
coinbase-api6
sqlalchemy6
postgresql6
classification6
virtualenv6
Programming languages (11)
Github contributions (5)
scikit-learn/scikit-learn
Apr 2015 - Jun 2017
scikit-learn: machine learning in Python
Role in this project:
Technical Writer
Technical WriterContributions:11 commits, 15 PRs, 21 comments in 2 years 2 months
Contributions summary:Preston primarily contributed to documentation within the scikit-learn repository. Their commits focused on refining grammar, clarifying wording, and correcting formatting inconsistencies in the documentation files. They made minor updates to improve clarity and consistency, including updating the naming convention and adding links to related projects. Their work indicates a focus on improving the user experience through better documentation.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
ClimbsRocks/chooseFunDates
Feb 2016 - May 2019
Contributions:29 pushes, 2 branches, 6 comments in 3 years 3 months
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